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Ability and utility of the Physician Well-Being Index to identify distress among Chinese physicians
1Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, the Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Background:
Despite the high prevalence of mental stress among physicians, reliable screening tools are scarce. This study aimed to evaluate the capability of the Physician Well-Being Index (PWBI) in identifying distress and adverse consequences among Chinese physicians.
Methods:
This cross-sectional online survey recruited 2803 physicians from Southern Mainland China via snowball sampling between October and December 2020. Data on socio-demographic characteristics, the PWBI, mental distress (including quality of life [QOL], burnout, sleepiness, fatigue and suicidal ideation) and adverse outcomes (medical errors and turnover intention) were collected. Chi-square tests and logistic regression were used for data analysis.
Results:
Seven items of the PWBI (emotional exhaustion, depression, stress, poor mental and physical QOL, low work meaning and dissatisfaction with work-life integration) were independently associated with low QOL (all p < 0.05). Physicians with lower QOL were more likely to endorse each item (OR: 1.76-5.86) and less likely to have favourable index scores (all p < 0.001). Assuming a prevalence of 29.2% for low QOL, the PWBI could reduce the post-test probability to 6.9% or increase it to 70.8%. Physicians scoring ≥4 on the PWBI were at increased risk (likelihood ratio >1) for experiencing various mental distress, with sensitivity exceeding 80% in detecting burnout, depression, high stress and anxiety. Additionally, the PWBI score helped stratify physicians' likelihood of reporting medical errors and turnover intention.
Conclusions:
This study provides preliminary insights into the validity and utility of the 9-item PWBI as a screening tool for assessing distress and well-being among Chinese physicians, helping identify those at higher risk of medical errors or turnover. However, these findings should be interpreted with caution due to the limited sample size.

